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DBMS > Fujitsu Enterprise Postgres vs. PlanetScale vs. QuestDB vs. Sphinx

System Properties Comparison Fujitsu Enterprise Postgres vs. PlanetScale vs. QuestDB vs. Sphinx

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Editorial information provided by DB-Engines
NameFujitsu Enterprise Postgres  Xexclude from comparisonPlanetScale  Xexclude from comparisonQuestDB  Xexclude from comparisonSphinx  Xexclude from comparison
DescriptionEnterprise-grade PostgreSQL-based DBMS with security enhancements such as Transparent Data Encryption and Data Masking, plus high-availability and performance improvement features.Scalable, distributed, serverless MySQL database platform built on top of VitessA high performance open source SQL database for time series dataOpen source search engine for searching in data from different sources, e.g. relational databases
Primary database modelRelational DBMSRelational DBMSTime Series DBMSSearch engine
Secondary database modelsDocument store
Spatial DBMS
Document store
Spatial DBMS
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.31
Rank#285  Overall
#129  Relational DBMS
Score1.59
Rank#151  Overall
#70  Relational DBMS
Score2.52
Rank#109  Overall
#9  Time Series DBMS
Score5.98
Rank#56  Overall
#5  Search engines
Websitewww.postgresql.fastware.complanetscale.comquestdb.iosphinxsearch.com
Technical documentationwww.postgresql.fastware.com/­product-manualsplanetscale.com/­docsquestdb.io/­docssphinxsearch.com/­docs
DeveloperPostgreSQL Global Development Group, Fujitsu Australia Software TechnologyPlanetScaleQuestDB Technology IncSphinx Technologies Inc.
Initial release202020142001
Current releaseFujitsu Enterprise Postgres 14, January 20223.5.1, February 2023
License infoCommercial or Open SourcecommercialcommercialOpen Source infoApache 2.0Open Source infoGPL version 2, commercial licence available
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageCGoJava (Zero-GC), C++, RustC++
Server operating systemsLinux
Windows
Docker
Linux
macOS
Linux
macOS
Windows
FreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Data schemeyesyesyes infoschema-free via InfluxDB Line Protocolyes
Typing infopredefined data types such as float or dateyesyesyesno
XML support infoSome form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.no
Secondary indexesyesyesnoyes infofull-text index on all search fields
SQL infoSupport of SQLyesyes infowith proprietary extensionsSQL with time-series extensionsSQL-like query language (SphinxQL)
APIs and other access methodsADO.NET
JDBC
native C library
ODBC
streaming API for large objects
ADO.NET
JDBC
MySQL protocol
ODBC
HTTP REST
InfluxDB Line Protocol (TCP/UDP)
JDBC
PostgreSQL wire protocol
Proprietary protocol
Supported programming languages.Net
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl
C infoPostgreSQL driver
C++
Go
Java
JavaScript (Node.js)
Python
Rust infoover HTTP
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
Server-side scripts infoStored proceduresuser defined functionsyes infoproprietary syntaxnono
Triggersyesyesnono
Partitioning methods infoMethods for storing different data on different nodespartitioning by range, list and by hashShardinghorizontal partitioning (by timestamps)Sharding infoPartitioning is done manually, search queries against distributed index is supported
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationMulti-source replication
Source-replica replication
Source-replica replication with eventual consistencynone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency across shards
Immediate Consistency within a shard
Immediate Consistency
Foreign keys infoReferential integrityyesyes infonot for MyISAM storage enginenono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACID at shard levelACID for single-table writesno
Concurrency infoSupport for concurrent manipulation of datayes, multi-version concurrency control (MVCC)yes infotable locks or row locks depending on storage engineyesyes
Durability infoSupport for making data persistentyesyesyesyes infoThe original contents of fields are not stored in the Sphinx index.
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyes infothrough memory mapped files
User concepts infoAccess controlfine grained access rights according to SQL-standardUsers with fine-grained authorization concept infono user groups or rolesno
More information provided by the system vendor
Fujitsu Enterprise PostgresPlanetScaleQuestDBSphinx
Specific characteristics100% compatible with community PostgreSQL
» more
Relational model with native time series support Column-based storage and time partitioned...
» more
Competitive advantagesBuilt-in TDE and Data Masking security. In-Memory Columnar Index, and a high speed...
» more
High ingestion throughput: peak of 4M rows/sec (TSBS Benchmark) Code optimizations...
» more
Typical application scenariosTransactional payments applications, reporting and mixed workloads.
» more
Financial tick data Industrial IoT Application Metrics Monitoring
» more
Key customersBanks & Hedge funds, Yahoo, OKX, Airbus, Aquis Exchange, Net App, Cloudera, Airtel,...
» more
Market metricsOver 30 years experience in database technology. Over 20 years in Postgres development...
» more
Licensing and pricing modelsCore based licensing
» more
Open source Apache 2.0 QuestDB Enterprise QuestDB Cloud
» more
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